You'll find the Future of Humanity Institute down a medieval backstreet in the centre of Oxford. It is beside St Ebbe's church, which has stood on this site since 1005, and above a Pure Gym, which opened in April. The institute, a research faculty of Oxford University, was established a decade ago to ask the very biggest questions on our behalf. Notably: what exactly are the "existential risks" that threaten the future of our species; how do we measure them; and what can we do to prevent them? Or to put it another way: in a world of multiple fears, what precisely should we be most terrified of? When I arrive to meet the director of the institute, Professor Nick Bostrom, a bed is being delivered to the second-floor office. Existential risk is a round-the-clock kind of operation; it sleeps fitfully, if at all. Bostrom, a 43-year-old Swedish-born philosopher, has lately acquired something of the status of prophet of doom among those currently doing most to shape our civilisation: the tech billionaires of Silicon Valley.

With so many people taking their cues from the movies on what a future with artificial intelligence will look like, some who fear one day having robotic overlords will be heartened by research that Google is doing. Google DeepMind, a London-based artificial intelligence company that Google acquired in 2014, is working on what will be a kill switch for robots and other A.I. systems. The idea is that one day a smart machine might be able to override its own off button. If that's the case, then humans would need another way to gain the upper hand. "If an agent is operating in real-time under human supervision, now and then it may be necessary for a human operator to press the big red button to prevent the agent from continuing a harmful sequence of actions -- harmful either for the agent or for the environment," researchers wrote in a paper posted on the Machine Intelligence Research Institute website.

In what could one day help find missing people in forests, a team of researchers used deep learning to train an autonomous drone to navigate a previously-unseen trail in a densely wooded forest completely on its own. The researchers from Dalle Molle Institute for Artificial Intelligence, the University of Zurich, and NCCR Robotics, mounted three GoPro cameras to a headset to train their deep neural network and took over 20,000 pictures from hours of trail hikes in the Swiss Alps. These images were then used alongside an NVIDIA GeForce GTX 580 GPU to teach the model what the boundaries of a hiking trail generally look like. Check out the autonomous drone in action in the video below. The researchers claim the resulting deep learning network is even better than humans at determining the correct direction of the trails on which it travels, guessing the correct direction of a trail with 85 percent accuracy.

There is no need to worry about whether robots might start taking our jobs. Three of the world's 10 largest employers are already replacing tens of thousands of their workers with robots: Foxconn, a key manufacturing partner for Apple, Google, and Amazon, is the world's 10th largest employer and it has already replaced 60,000 workers with robots, according to a recent note written in part by analyst John Seagrimat CLSA. Walmart, the third-largest global employer with 2.1 million workers, wants to replace its warehouse stock-checkers with flying drones that can scan miles of shelves in a fraction of the time. And the US Department of Defense, the No.1 global employer, is already; flying the world's largest fleet of unmanned aerial vehicles - drones, basically - in its various Middle East conflicts. The US DoD has at least 7,362 RQ-11 Ravens in operation for instance.

In U.S. Congress Discusses AI, Automation, Robotics and Basic Income we see senior U.S. Government people start to try and understand the changing world… Nikolas Badminton is a world-respected futurist speaker that researches, speaks, and writes about the future of work, how technology is affecting the workplace, how workers are adapting, the sharing economy, and how the world is evolving. He appears at conferences in Canada, USA, UK, and Europe. Email him to book him for your radio, TV show, or conference.

Further, recent psychoacoustical evidence suggest the approach bears some resemblance with human auditory processing for sound textures (McDermott et al., 2013; Nelken and de Cheveigné, 2013). In an influential 2007 article, Aucouturier, Defreville & Pachet (Aucouturier et al., 2007) applied a BOF model to categorize both polyphonic music and soundscapes. Their results showed that, while BOF was a meriting model for their polyphonic music dataset, it was spectacularly effective for soundscapes, reaching accuracies of 96%. The contrast, they interpreted, lied in differences in the temporal structure of both types of stimuli, with music being more formally organized and soundscapes more easily summarized by statistics. In a later companion study (Aucouturier and Defreville, 2009), they showed that soundscapes could be time-shuffled without altering listeners' perception of their acoustic similarity, while music could not. While more work was needed for music, the authors therefore concluded that BOF was a sufficient model to approximate human perception for soundscapes, practically ruling out the need to recognize the local acoustic events in a texture in order to identify it.

We present a new framework for online Least Squares algorithms for nonlinear modeling in RKH spaces (RKHS). Instead of implicitly mapping the data to a RKHS (e.g., kernel trick), we map the data to a finite dimensional Euclidean space, using random features of the kernel's Fourier transform. The advantage is that, the inner product of the mapped data approximates the kernel function. The resulting "linear" algorithm does not require any form of sparsification, since, in contrast to all existing algorithms, the solution's size remains fixed and does not increase with the iteration steps. As a result, the obtained algorithms are computationally significantly more efficient compared to previously derived variants, while, at the same time, they converge at similar speeds and to similar error floors.

A sequel about married paranormal investigators, "The Conjuring 2," ascended to the top of the Friday box office, outperforming runners-up "Warcraft" and "Now You See Me 2." The three debuts supplanted last week's box-office leader "Teenage Mutant Ninja Turtles: Out of the Shadows," which landed in the fourth spot, followed by the Warner Bros. romance "Me Before You." "The Conjuring 2" earned an estimated 16.4 million overnight. The New Line/Warner Bros. film exceeded expectations while on its way to a projected 40 million opening weekend. Though hardly a disappointment, the sequel has a steep climb to reach the tally of its predecessor, which ultimately earned nearly 320 million worldwide. Audiences liked the movie, which stars Vera Farmiga and Patrick Wilson as believers working to exorcise demons from a home in North London. Like its predecessor, the second installment earned an A- from the polling firm CinemaScore.

It's no mystery that big data presents a challenge to privacy. But perhaps more alarming is the emergence of technology that combines facial recognition and data analytics to create a powerful surveillance tool. It's a disturbing development that combines the most worrisome aspects of algorithmic and big data technology with the chilling and dangerous threats inherent in facial recognition. A Chicago tech company is advertising its "predictive video" to anticipate behavior "based on the emotional state and personality style of any person in a video." In Russia, the app FindFace gives users "the power to identify total strangers on the street," according to The Atlantic. Google's new chat app Allo has a "smart reply" feature that apparently analyzes photos from contacts and offers suggested responses to them .

"The future is here," or so stated Adrian Flux Insurance Services, an insurance broker out of Norfolk, England, that announced it will issue policies for self-driving cars. "Unlike every insurance policy that you've ever held in the past, driverless car insurance needs to cover you against a whole host of modern problems, not just your typical bumps and scrapes," the company stated in a news release. The U.K. allows the extensive testing of fully autonomous vehicles on public roads, as do the states of California, Florida, Michigan, Nevada, Texas and the District of Columbia in the U.S. New vehicles are increasingly coming with advanced driver assistance systems (ADAS), which can take control of the vehicle to ensure it stops before hitting an object or maintains speed and distance between other vehicles. Google's self-driving pod car has no steering wheel. California is considering regulations that would require a human driver behind every autonomous vehicle's steering wheel.